Published in the February 2008 issue of Today’s Facility Manager
The performance of HVAC equipment is crucial in all facilities. The scope of functions that these machines perform can affect virtually all areas of a building.
While routine maintenance checks are often completed as part of an HVAC service program, they don’t always identify problems that can lead to machine failure. On the other hand, predictive maintenance analyzes current equipment conditions and dictates tasks that must be completed to keep machines running at optimum levels. Implementing a predictive maintenance plan can extend equipment life and improve a company’s bottom line.
More Than Problem Diagnosis
Most facility managers (fms) are familiar with predictive maintenance and how it can be used to analyze machine condition. However, many employ predictive maintenance testing only after an equipment problem has already occurred and the cause must be diagnosed. By including predictive technology as part of routine maintenance, fms could monitor machines frequently, anticipating potential problems before they lead to serious equipment damage.
Subscribing to the school of thought that a good preventive program is enough to maintain equipment, few are willing to add predictive diagnostics to their maintenance plan. Old habits can be difficult to change.
Another barrier to more widespread adoption of predictive technology is the fear of negative test results. The initial predictive test often reports many problems, especially when only deferred maintenance has been practiced in the past. As a result, many fms may be hesitant to put their HVAC systems through predictive tests.
But instead of becoming a cause for alarm, reports can be used to put problems in perspective and prioritize where repair efforts should be concentrated. Test results can establish benchmarks for machine performance. These results can then be used to compare against progress and evaluated to make changes to the maintenance plan. A good predictive maintenance plan allows for equipment re-examination and results tracking to optimize the repair process and ensure repairs are performed correctly.
A lack of experience with predictive diagnostics also prevents some fms from adopting the technology into their maintenance strategies. This is especially common when these diagnostics are used only to identify an equipment problem. One solution is to outsource the predictive maintenance and benefit from the presence of technicians who are trained and are proficient at analyzing data quickly. Continued expert analysis can improve equipment reliability, which reduces maintenance and energy costs.
Transitioning To Condition Based Maintenance
A more common maintenance practice is preventive, which is typically time based. Examples include conducting a machine teardown after 5,000 hours of runtime or replacing a part every six months. In contrast, predictive maintenance uses data collected from equipment to measure machine condition and generate tasks only when they must be performed, resulting in less time spent making unneeded repairs. Over time, results can then be used to develop a condition based maintenance plan.
Of course, the best plans have a balance of both preventive and predictive technology. Some tasks, such as inspecting guards, doors, and covers, are cheaper to maintain on a time schedule, because an alternative predictive technology is not available. Other tasks, such as relubricating bearings might not need to be performed as frequently as the time schedule dictates.
Predictive Diagnostics For HVAC Equipment
The most common predictive technologies used for HVAC applications are vibration and oil analysis. Frequently used in compressors, vibration analysis gathers structural vibration data from multiple locations on the compressor and compares it to either manufacturer specifications or other databased machines of similar configuration to identify abnormal vibration patterns. Problems, such as excess noise or machine vibration, can be caused by poor installation, internal machine defects, or machine wear and tear. Once the vibration data has been collected, the problem can be isolated, fixed, and rechecked to verify the solution is effective.
Oil analysis, often used in chillers, can determine which part of the machine is experiencing significantly harmful wear. Contaminants affecting chiller operation can also be detected. Added benefits of oil analysis include reduced frequency of oil changes, which improves lubrication control and increases equipment life.
Other HVAC predictive technologies include: misalignment and balance service to prevent bearing failure; lithium bromide analysis to keep absorber chiller evaporators operating at peak performance; electrical analysis to determine motor condition; refrigerant analysis to maintain optimal cooling systems performance; water treatment service to prevent equipment corrosion; and root cause failure analysis to determine conclusively the reason for machine failure.
Improving The Bottom Line
Although the upfront costs of a predictive maintenance plan may be higher than a traditional preventive plan, lower costs will eventually be realized through optimized maintenance programs, extended equipment life, and improved reliability.
Predictive services can identify machine faults before they lead to catastrophic failure. This allows for planned equipment repairs instead of costly emergency fixes. In addition, downtime can be scheduled to maintain productivity.
Incorporating predictive technology into facility maintenance plans reduces capital and operational costs. This can positively impact the equipment, and the facility as a whole.
As manager of predictive diagnostics at Johnson Controls, Kuchler has more than 20 years of experience with predictive maintenance programs. In his current role, he oversees predictive services including data analysis, report generation, and repair assistance in North America, South America, South East Asia, and Australia. Kuchler holds certifications in category three vibration from the Vibration Institute and level one machinery lubrication from the International Council for Machinery Lubrication.